From ambiguous problem to
production AI system
Senior, founder-led engineering for organizations that need AI to work in production — not just in a demo. We scope honestly, build pragmatically, and measure everything against ground truth.
What we deliver
Four practice areas, one standard: systems that hold up in production.
Agentic & Multi-Agent LLM Systems
We design and deploy LLM systems that plan, use tools, and coordinate multi-step workflows autonomously — with orchestration, guardrails, and evaluation frameworks that make them trustworthy. Ideal for document-heavy operations, research automation, and workflow intelligence.
- Multi-agent orchestration with LangChain & LangGraph
- Workspace, coding, and review agents for internal platforms
- Cross-document validation and agentic arbitration
- Evaluation & experimentation frameworks benchmarked to ground truth
Document Intelligence & RAG
End-to-end pipelines that convert heterogeneous document corpora into structured, queryable data — the same discipline behind our federal-scale patent-trial processing system.
- Ingestion, parsing, chunking, indexing, and structured extraction
- Hybrid PDF extraction: native text layer, traditional OCR, LLM-based OCR
- RAG, vector search, semantic ranking, and knowledge-graph reasoning
- Context reduction and token-efficiency optimization at scale
Machine Learning & Predictive Analytics
Custom models and the data infrastructure around them — from experiment to deployed, monitored system.
- Transformers, LSTMs, NLP, time-series, and anomaly detection
- Geospatial, financial, and on-chain analytics
- Scalable pipelines with Beam/Dataflow, Spark, BigQuery, and Airflow
- Cloud-native training and serving on GCP
Full-Stack AI Product Engineering
ML backends wired to interfaces people actually use — designed, built, and deployed to autoscale.
- Serverless and containerized deployments (App Engine, Cloud Run, GKE)
- Autoscaling LLM inference architectures
- Responsive web applications and internal tools
- Multimodal systems: speech, image, and 3D generation pipelines
How engagements run
A pragmatic path from idea to production — no six-month discovery phases.
Scope
A focused consultation to map your problem to the right technique — or tell you plainly if AI isn't the answer. You leave with an honest assessment and a concrete plan.
Prove
A working prototype against your real data, with an evaluation harness from day one. We establish ground truth early so progress is measured, not vibes-based.
Productionize
Harden, deploy, and document. Guardrails, monitoring, and clean handoff — or ongoing partnership as your AI subject-matter expert.
Why MEZTech
You work directly with the engineer who builds your system.
Founder-led, senior-only
No handoffs to junior staff. Every engagement is led directly by senior engineers with production agentic systems running at scale.
Evaluation-driven
We build evaluation frameworks against curated ground truth before scaling — the difference between an impressive demo and a dependable system.
We ship our own products
bib-q.com, junkscape.app, and optviz.com were conceived, built, and are operated by us. We hold client work to the same standard.
Have a problem worth automating?
Tell us what you're building. We'll respond within 24 hours with an honest read on approach, feasibility, and cost.
Start a project